Fluctuation dynamics of a single magnetic chain

"Tunable" fluids such as magnetorheological "MR" and electrorheological "ER" fluids are comprised of paramagnetic or dielectric particles suspended in a low-viscosity liquid. Upon the application of a magnetic or electric field, these fluids display a dramatic, reversible, and rapid increase of the viscosity. This change in viscosity can, in fact, be tuned by varying the applied field, hence the name "tunable fluids". This effect is due to longitudinal aggregation of the particles into chains in the direction of the applied field and the subsequent lateral aggregation into larger semisolid domains. A recent theoretical model by Halsey and Toor "HT" explains chain aggregation in dipolar fluids by a fluctuation-mediated long-range interaction between chains and predicts that this interaction will be equally efficient at all applied fields. This paper describes video-microscopy observations of long, isolated magnetic chains that test HT theory. The measurements show that, in contrast to the HT theory, chain aggregation occurs more efficiently at higher magnetic field strength (H0) and that this efficiency scales as H0½. Our experiments also yield the steady-state and time-dependent fluctuation spectra C(x,x')≡ [h(x)-h(x')]²>½ and C(x,x',t,t')≡ ½ for the instantaneous deviation h(x,t) from an axis parallel to the field direction to a point x on the chain. Results show that the steady-state fluctuation growth is similar to a biased random walk with respect to the interspacing ͉ |x-x'| along the chain, C(x,x')≈|x-x'| α, with a roughness exponent α =0.53±0.02. This result is partially confirmed by Monte Carlo simulations. Time-dependent results also show that chain relaxation is slowed down with respect to classical Brownian diffusion due to the magnetic chain connectivity, C(x,x',t,t')≈|t-t'|β, with a growth exponent β=0.35±0.05<½. All data can be collapsed onto a single curve according to C(x,x',t,t')≈|x-x'| α ψ (|t-t'| / |x-x'| z ), with a dynamic exponent z= α /β≅ 1.42

A mechanism of coupling RCC1 mobility to RanGTP production on the chromatin in vivo

The RanGTP gradient across the interphase nuclear envelope and on the condensed mitotic chromosomes is essential for many cellular processes, including nucleocytoplasmic transport and spindle assembly. Although the chromosome-associated enzyme RCC1 is responsible for RanGTP production, the mechanism of generating and maintaining the RanGTP gradient in vivo remains unknown. Here, we report that regulator of chromosome condensation (RCC1) rapidly associates and dissociates with both interphase and mitotic chromosomes in living cells, and that this mobility is regulated during the cell cycle. Our kinetic modeling suggests that RCC1 couples its catalytic activity to chromosome binding to generate a RanGTP gradient. Indeed, we have demonstrated experimentally that the interaction of RCC1 with the chromatin is coupled to the nucleotide exchange on Ran in vivo. The coupling is due to the stable binding of the binary complex of RCC1–Ran to chromatin. Successful nucleotide exchange dissociates the binary complex, permitting the release of RCC1 and RanGTP from the chromatin and the production of RanGTP on the chromatin surface

Organization of Cellular Receptors into a Nanoscale Junction during HIV-1 Adhesion

The fusion of the human immunodeficiency virus type 1 (HIV-1) with its host cell is the target for new antiretroviral therapies. Viral particles interact with the flexible plasma membrane via viral surface protein gp120 which binds its primary cellular receptor CD4 and subsequently the coreceptor CCR5. However, whether and how these receptors become organized at the adhesive junction between cell and virion are unknown. Here, stochastic modeling predicts that, regarding binding to gp120, cellular receptors CD4 and CCR5 form an organized, ring-like, nanoscale structure beneath the virion, which locally deforms the plasma membrane. This organized adhesive junction between cell and virion, which we name the viral junction, is reminiscent of the well-characterized immunological synapse, albeit at much smaller length scales. The formation of an organized viral junction under multiple physiopathologically relevant conditions may represent a novel intermediate step in productive infection

Search for temporal cell segmentation robustness in phase-contrast microscopy videos

Proceeding of: Medical Imaging with Deep Learning (MIDL 2022), Zürich, Switzerland, 6-8 July 2022This work presents a deep learning-based workflow to segment cancer cells embedded in D collagen matrices and imaged with phase-contrast microscopy under low magnification and strong background noise conditions. Due to the experimental and imaging setup, cell and protrusion appearance change largely from frame to frame. We use transfer learning and recurrent convolutional long-short term memory units to exploit the temporal information and provide temporally stable results. Our results show that the proposed approach is robust to weight initialization and training data sampling.This work was co-financed by ERDF, "A way of making Europe" (AMB), partially funded under Grant PID2019-109820RB-I00, MCIN/AEI/10.13039/501100011033/; the US NIH under Grants UO1AG060903 (DW) and U54CA143868 (DW). We acknowledge NVIDIA Corporation for the donation of the Titan X (Pascal) GPU

Three-Dimensional Matrix Fiber Alignment Modulates Cell Migration and MT1-MMP Utility by Spatially and Temporally Directing Protrusions

Multiple attributes of the three-dimensional (3D) extracellular matrix (ECM) have been independently implicated as regulators of cell motility, including pore size, crosslink density, structural organization, and stiffness. However, these parameters cannot be independently varied within a complex 3D ECM protein network. We present an integrated, quantitative study of these parameters across a broad range of complex matrix configurations using self-assembling 3D collagen and show how each parameter relates to the others and to cell motility. Increasing collagen density resulted in a decrease and then an increase in both pore size and fiber alignment, which both correlated significantly with cell motility but not bulk matrix stiffness within the range tested. However, using the crosslinking enzyme Transglutaminase II to alter microstructure independently of density revealed that motility is most significantly predicted by fiber alignment. Cellular protrusion rate, protrusion orientation, speed of migration, and invasion distance showed coupled biphasic responses to increasing collagen density not predicted by 2D models or by stiffness, but instead by fiber alignment. The requirement of matrix metalloproteinase (MMP) activity was also observed to depend on microstructure, and a threshold of MMP utility was identified. Our results suggest that fiber topography guides protrusions and thereby MMP activity and motility

Actin cap associated focal adhesions and their distinct role in cellular mechanosensing

The ability for cells to sense and adapt to different physical microenvironments plays a critical role in development, immune responses, and cancer metastasis. Here we identify a small subset of focal adhesions that terminate fibers in the actin cap, a highly ordered filamentous actin structure that is anchored to the top of the nucleus by the LINC complexes; these differ from conventional focal adhesions in morphology, subcellular organization, movements, turnover dynamics, and response to biochemical stimuli. Actin cap associated focal adhesions (ACAFAs) dominate cell mechanosensing over a wide range of matrix stiffness, an ACAFA-specific function regulated by actomyosin contractility in the actin cap, while conventional focal adhesions are restrictively involved in mechanosensing for extremely soft substrates. These results establish the perinuclear actin cap and associated ACAFAs as major mediators of cellular mechanosensing and a critical element of the physical pathway that transduce mechanical cues all the way to the nucleus

Use of the p-values as a size-dependent function to address practical differences when analyzing large datasets

Biomedical research has come to rely on p-values as a deterministic measure for data-driven decision-making. In the largely extended none hypothesis significance testing for identifying statistically significant differences among groups of observations, a single p-value is computed from sample data. Then, it is routinely compared with a threshold, commonly set to 0.05, to assess the evidence against the hypothesis of having non-significant differences among groups, or the none hypothesis. Because the estimated p-value tends to decrease when the sample size is increased, applying this methodology to datasets with large sample sizes results in the rejection of the none hypothesis, making it not meaningful in this specific situation. We propose a new approach to detect differences based on the dependence of the p-value on the sample size. We introduce new descriptive parameters that overcome the effect of the size in the p-value interpretation in the framework of datasets with large sample sizes, reducing the uncertainty in the decision about the existence of biological differences between the compared experiments. The methodology enables the graphical and quantitative characterization of the differences between the compared experiments guiding the researchers in the decision process. An in-depth study of the methodology is carried out on simulated and experimental data. Code availability at https://github.com/BIIG-UC3M/pMoSS.This work was supported by Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación, under Grants TEC2015-73064-EXP, TEC2016-78052, and PID2019-109820RB-I00, MCIN/AEI/10.13039/501100011033/, co-fnanced by European Regional Development Fund (ERDF), "A way of making Europe" (AMB); BBVA Foundation under a 2017 Leonardo Grant for Researchers and Cultural Creators (AMB); the US National Institutes of Health under Grants UO1AG060903 (DW, JMP), P30AG021334 (JMP) and U54CA143868 (DW); the National Science Foundation Graduate Research Fellowship under Grant No. 1746891 (AS, DW). We also want to acknowledge the support of NVIDIA Corporation with the donation of the Titan X (Pascal) GPU used for this research. We thank Claire Jordan Brooks, Prof. Joachim Goedhart (University of Amsterdam), Laura Nicolás-Sáenz, Pedro Macías-Gordaliza and Prof. Naomi Altman (Pennsylvania State University) for their constructive comments and fruitful discussions

Mechanotransductive feedback control of endothelial cell motility and vascular morphogenesis

Vascular morphogenesis requires persistent endothelial cell motility that is responsive to diverse and dynamic mechanical stimuli. Here, we interrogated the mechanotransductive feedback dynamics that govern endothelial cell motility and vascular morphogenesis. We show that the transcriptional regulators, YAP and TAZ, are activated by mechanical cues to transcriptionally limit cytoskeletal and focal adhesion maturation, forming a conserved mechanotransductive feedback loop that mediates human endothelial cell motility in vitro and zebrafish intersegmental vessel (ISV) morphogenesis in vivo. This feedback loop closes in 4 hours, achieving cytoskeletal equilibrium in 8 hours. Feedback loop inhibition arrested endothelial cell migration in vitro and ISV morphogenesis in vivo. Inhibitor washout at 3 hrs, prior to feedback loop closure, restored vessel growth, but washout at 8 hours, longer than the feedback timescale, did not, establishing lower and upper bounds for feedback kinetics in vivo. Mechanistically, YAP and TAZ induced transcriptional suppression of myosin II activity to maintain dynamic cytoskeletal equilibria. Together, these data establish the mechanoresponsive dynamics of a transcriptional feedback loop necessary for persistent endothelial cell migration and vascular morphogenesis

Effect of modifying quantum dot surface charge on airway epithelial cell uptake in vitro

Abstract The respiratory system is one of the portals of entry into the body, and hence inhalation of engineered nanomaterials is an important route of exposure. The broad range of physicochemical properties that influence biological responses necessitate the systematic study to contribute to understanding occupational exposure. Here, we report on the influence of nanoparticle charge and dose on human airway epithelial cells, and show that this platform can be used to evaluate consequences of exposure to engineered nanomaterials